Enhanced Database Failover for High-Availability AI Systems

Question

Pulumi · Accepted Answer

In a high-availability AI system, you generally need a robust and fault-tolerant database setup. Enhanced database failover ensures that if your primary database instance fails for any reason, traffic can be automatically redirected to a standby instance with minimal disruption.

For our example, we will use the `azure-native.sql.InstanceFailoverGroup` resource from Azure to manage high availability for Azure SQL databases. An Instance Failover Group in Azure allows you to manage replication and failover of a group of databases from a primary Azure SQL Database server to a secondary server. By doing this, you can ensure that if the primary server becomes unavailable, the secondary can take over, minimizing downtime.

Here is a Python program using Pulumi that sets up an enhanced database failover for high-availability AI systems:

```python
import pulumi
import pulumi_azure_native as azure_native

# Assuming you have two Azure SQL managed instances in different regions for high-availability, 
# the primary and secondary instances. We also assume that the local and remote resource group names,
# as well as the local and remote SQL managed instance names are already known.

# Define the instance failover group
instance_failover_group = azure_native.sql.InstanceFailoverGroup(
    "instanceFailoverGroup",
    resource_group_name="primaryResourceGroupName",  # Resource group of the primary instance
    location_name="primaryLocation",                # Location of the primary instance
    managed_instance_pairs=[{
        "partner_managed_instance_id": "/subscriptions/{subscriptionId}/resourceGroups/{secondaryResourceGroupName}/providers/Microsoft.Sql/managedInstances/{secondarySqlManagedInstanceName}",  # Partner (secondary) managed instance ID
        "primary_managed_instance_id": "/subscriptions/{subscriptionId}/resourceGroups/{primaryResourceGroupName}/providers/Microsoft.Sql/managedInstances/{primarySqlManagedInstanceName}",    # Primary managed instance ID
    }],
    read_write_endpoint={
        "failover_policy": "Automatic",              # Set to "Automatic" for automatic failover
        "failoverWithDataLossGracePeriodMinutes": 60 # Grace period before failover with data loss
    },
    partner_regions=[{
        "location": "secondaryLocation"              # Location of the secondary instance
    }],
)

# Export the read/write listener endpoint of the failover group
pulumi.export("readWriteListenerEndpoint", instance_failover_group.read_write_listener_endpoint)
```

In the provided code:
- We're creating an instance of Azure SQL Database Failover Group called `instanceFailoverGroup`.
- We specify the resource group name and location of the primary SQL managed instance.
- `managed_instance_pairs` defines the primary and secondary SQL managed instances which are part of the failover process.
- The `read_write_endpoint` configuration specifies that the failover process should be automatic and sets a grace period of 60 minutes before failover with potential data loss.
- We are also defining `partner_regions` to be the location of the secondary SQL managed instance.
- Finally, we're exporting the read/write listener endpoint of the failover group so we can easily retrieve the connection endpoint after deployment.

To use the above program, you need to replace placeholder values like:
- `primaryResourceGroupName` with the actual name of the resource group containing your primary SQL managed instance,
- `secondaryResourceGroupName` with the name of the resource group containing the secondary SQL managed instance,
- `primaryLocation` with the Azure region of your primary SQL managed instance, and
- `secondaryLocation` with the Azure region of your secondary SQL managed instance.

Please make sure you have the right to access and manage Azure resources and also to configure the appropriate settings in both Azure SQL instances for failover to work as expected.

Once the Pulumi program is complete and successfully deployed, your AI systems will have a high-availability database configuration with automatic failover capabilities, which is a critical component for maintaining uptime and reliability.